Ubc13: the Lys63 ubiquitin chain building machine
Bibliographic record
Abstract
// Curtis D. Hodge 1 , Leo Spyracopoulos 1 and J. N. Mark Glover 1 1 Department of Biochemistry, University of Alberta, Edmonton, Alberta, Canada Correspondence to: J. N. Mark Glover, email: // Keywords : Ubc13, ubiquitination, Mms2, Uev1A, RING E3 ligase Received : June 01, 2016 Accepted : July 19, 2016 Published : July 29, 2016 Abstract Ubc13 is an ubiquitin E2 conjugating enzyme that participates with many different E3 ligases to form lysine 63-linked (Lys63) ubiquitin chains that are critical to signaling in inflammatory and DNA damage response pathways. Recent studies have suggested Ubc13 as a potential therapeutic target for intervention in various human diseases including several different cancers, alleviation of anti-cancer drug resistance, chronic inflammation, and viral infections. Understanding a potential therapeutic target from different angles is important to assess its usefulness and potential pitfalls. Here we present a global review of Ubc13 from its structure, function, and cellular activities, to its natural and chemical inhibition. The aim of this article is to review the literature that directly implicates Ubc13 in a biological function, and to integrate structural and mechanistic insights into the larger role of this critical E2 enzyme. We discuss observations of multiple Ubc13 structures that suggest a novel mechanism for activation of Ubc13 that involves conformational change of the active site loop.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".